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Purpose: Exosomes are ubiquitous extracellular vesicles secreted during diseased and physiological conditions. Exosomal RNA has been associated with cancer development and progression. Enriching clinically relevant tissue-specific exosomes may assist in focusing more on key RNA molecules packaged during cancer, but the current exosome isolation methods isolate total exosomes. Therefore, this study focused on isolating lung cancer cell-derived exosomes to get insights into the altered biology of the disease. Method: We developed a rapid immunomagnetic exosome enrichment method that enables the separation of lung cancer cell-derived exosomes from human plasma. The total RNA purified from these immunomagnetically enriched exosomes was characterized using a high throughput sequencing to profile the different RNA biotypes packaged and their differential expression in these exosomes. Further, functional enrichment was performed to determine the functional annotation terms significantly correlated with the list of identified differentially expressed genes (DEGs). Results: In total, 1383 mRNAs and 64 lncRNA were identified as differentially expressed between patient plasma exosomes than healthy controls (fold change > 2, P < 0.05). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the DEGs were mainly enriched in the cancer-related pathways, purine metabolism, calcium and cGMP-PKG (cyclic-guanosine 3’,5’monophosphate-protein kinase G) signaling pathways.Conclusion: The method developed here provided adequate RNA quality for high throughput sequencing. The total transcriptome analysis of lung cancer cell-derived exosomes revealed that the majority of DEGs were involved in cancer-related pathways suggesting that this method could be further utilized to identify disease-specific exosome biomarkers for liquid biopsy-based diagnostic applications.

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Nanoparticles are used in various biomedical applications like in vitro diagnostics, imaging, drug delivery, and other therapeutic uses. The performance of such applications requires accurate knowledge of size distribution that needs precise characterization techniques. In this study, a single‐nanoparticle characterization system based on the total internal reflected scattering signal (SNC‐TIRS) is demonstrated for the size estimation of synthetic nanoparticles and exosomes. A compact waveguide‐based evanescent field illumination is used to convert a digital microscope into a nanoparticle characterization system based on scattering signals from diffusing nanoparticles in Brownian motion. By analyzing single‐particle trajectories, the system estimates the hydrodynamic size, average number of particles observed per unit volume, and the distribution of sample heterogeneity. SNC‐TIRS is benchmarked with inorganic nanoparticles and biomaterials in size range of 80–250 nm. Its utility to characterize the size of exosomes isolated from plasma using magnetic nanoparticles (MNPs) is shown. The hydrodynamic size of bare MNPs (123.83 ± 29.19 nm), antibody‐bound‐MNPs (161.33 ± 29.47 nm), and antibody‐exosome‐bound‐MNP conjugates (224.82 ± 25.89) are estimated and the results obtained agree with standard methods such as dynamic light scattering and nanoparticle tracking analysis. SNC‐TIRS can enable the label‐free characterization of nanomaterials and clinically relevant biomarkers.